getting fat on government cheese: the connection between

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45

Getting Fat on Government Cheese: The Connection Between Social Welfare Participation, Gender, and Obesity in America

MICHAEL CORRELL*

ABSTRACT

The dramatic increase in obese and overweight Americans over the last two decades has produced enormous scholarly interest. New theories as to the causes, medical consequences, and legal implications of obesity abound. Despite this increase in obesity scholarship, medical, legal, and social science understandings of this topic largely remain segregated by field. This article attempts to accomplish an intersectional analysis of a discrete portion of recent scholarship in an effort to reveal otherwise indiscernible causes and consequences of obesity.

Currently, the available medical scholarship focuses almost exclusively on either single-characteristic empirical analysis or tracking health outcomes. The limited social science literature on this topic is generally focused on assessing the advance of obesity as a stigmatizing force in society but tends to avoid issues of causation altogether. Finally, the legal scholarship in this area centers on issues of feminism and potential judicial development of antidiscrimination law. To overcome this insulation, this article applies an intersectional approach to 1) demonstrate the problem of increased obesity in impoverished women; 2) trace this problem to specific policy failures promoting obesity in this specific group; 3) evaluate the medical, social, and legal consequences of these policy failures; and 4) propose policy reforms on the basis of the combined recommendations set forth in medical, legal, and social science literature.

Specifically, the insular nature of obesity scholarship has obscured the important connections between gender, poverty, and obesity. This article posits that this insulation obscures important policy failures in the Food Stamps program and Temporary Aid to Needy Families (TANF) program that promote obesity in poor women. These policy failures impose increased medical hardship, generate social stigma preventing escape from poverty, and erode the protections of Title VII afforded to poor women. This article argues that the Food Stamps Program and TANF must be revisited and reassessed to eliminate the obesity-inducing food insecurity, temporal poverty, and unhealthy food selection each program currently promotes.

* Associate, Jones Day; J.D., Stanford Law School; B.A., Southern Methodist University. Special thanks to my wife Tori for all of her editorial help along the way.

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46 DUKE JOURNAL OF GENDER LAW & POLICY Volume 18:45 2010

I. INTRODUCTION

The obesity epidemic1 rapidly spreading through every part of American society has been examined in a variety of ways. Prevalence of the disease—affecting as many as 72 million Americans2—has been associated with age, race, and socioeconomic status. Yet one significant risk factor has been almost uniformly ignored outside a small group of medical studies. That factor is gender. The majority of obese Americans are women, or, more precisely, poor women. Though the margins vary, Caucasian, African American, and Hispanic women with limited economic resources outpace their male counterparts in epidemiological surveys of obesity.3 What’s more, this increased incidence of obesity in women holds for almost every age group.4 Despite this readily apparent gender asymmetry, biological differences alone simply cannot explain why women are more prone to clinical obesity.

If no innate trait fully accounts for these statistical variations, then perhaps the risk factor promoting obesity in women is not biologically related to gender at all but, rather, environmentally driven in ways uniquely associated with gender. As women move out of poverty, the prevalence of obesity becomes almost inversely proportional to income in every race and age group despite failing to produce a similar impact in men.5 This article posits that the increased rate of obesity observed in women with limited economic resources results as a direct consequence of a series of unique social policy pressures imposed almost exclusively upon impoverished women by America’s most basic social welfare policies.

Section II will examine the relationship between gender and other risk factors for obesity as represented in statistical epidemiology surveys conducted by the Centers for Disease Control (CDC) and the U.S. Department of Health and Human Services (DHHS). I will discuss the links between obesity, gender, and socioeconomic status as well as several other contributing factors in an effort to illuminate the important hidden risk factors driving the spread of this disease through the ranks of America’s least advantaged women.

Section III will consider four potential policy-driven explanations for the divergence between the male and female obesity rates at or around the poverty line. Specifically, I will examine the following policy failures giving rise to increased obesity in poor women: 1) failure of the Food Stamps program to promote healthy eating and access to healthy foods; and 2) the negative impact of the Temporary Aid to Needy Families program on food security and the

1. See infra Section II.A for a more detailed definition of obesity. For the purposes of this article, the term “obesity” should be understood to generally refer to the condition of maintaining a body mass index (BMI) greater than 30. Though meriting similar evaluation, this article will not consider the very different situation of those Americans classified only as “overweight.” 2. Press Release, Ctrs. for Disease Control & Prevention, New CDC Study Finds No Increase in Obesity Among Adults; But Levels Still High (Nov. 28, 2007), available at http://www.cdc.gov/nchs/ PRESSROOM/07newsreleases/obesity.htm. 3. NAT’L CTR. FOR HEALTH STATISTICS, HEALTH 289 (2007). 4. Id. 5. Virginia W. Chang, U.S. Obesity, Weight Gain, and Socioeconomic Status, 3 CENTER FOR

HEALTH EQUITY RES. AND PROMOTION, POL’Y BRIEF 2 (2005), available at http://www.cherp.org/ cherpdocs/issuebriefs/Policy%20Brief_Fall2005.pdf.

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GETTING FAT ON GOVERNMENT CHEESE 47

availability of non-employment time for activities such as meal preparation and exercise.

Section IV will examine the medical, legal, and social consequences attached to obesity in women. In particular, I will consider 1) obesity’s hidden medical difficulties specifically affecting women; 2) the added social obstacles imposed upon obese women limiting economic and social advancement; and 3) the implications of obesity discrimination as a form of subtle gender discrimination circumventing the important protections secured by Title VII of the Civil Rights Act of 1964.

Section V will conclude with recommendations aimed at transforming social welfare policies that actually promote obesity in poor women into programs reversing the spread of America’s deadly new epidemic.

II. THE SCOPE AND SOURCE OF THE GENDER-OBESITY ISSUE

Obesity in America, both as a social disease and frequent headline, is oversimplified by its popular conception. Though important and relevant to this discussion, commonly discussed aggregate numbers and even simple breakdowns along gender lines belie the complexity of this modern epidemic. Instead, the key to identifying and remedying the root causes of obesity turns on a careful review of the intersections of various empirical data sets collected by the DHHS, through the offices of the CDC and the National Institutes of Health, various scholars publishing their findings in peer reviewed journals, and even the United States Census Bureau.6

The data collected by these organizations shows, in short, that the differences observed in male and female obesity rates cannot be attributed to mere biology. That is not to say there are no genetic, pathological, or otherwise biological causes contributing to American obesity.7 The prevalence of these characteristics, however, pales in comparison to obesity’s primary cause—caloric imbalance.8 Biology, while critical to the study of obesity in general, simply fails to comprehensively explain the differences observed in men and women.

Instead, the absolute dominance of caloric imbalance as the primary cause of obesity and the consistent divergence in male/female obesity rates suggests that some other factor is causing both greater and more frequent over-consumption and/or insufficient exertion in women. Yet only one factor considered in the array of available empirical studies explains this correlation—poverty. Women of all ages and races experience obesity at a higher rate than men.9 Obesity consistently declines in women as income increases and vice-

6. See NAT’L CTR. FOR HEALTH STATISTICS, supra note 3; Cynthia L. Ogden et al., Prevalence of Overweight and Obesity in the United States 1999-2004, 295 JAMA, 1549 (2006); U.S. CENSUS BUREAU, ANNUAL SOCIAL AND ECONOMIC SUPPLEMENT (2005), available at http://www.bls.census.gov/cps/ asec/2005/sdata.htm. 7. Overweight and Obesity: Causes and Consequences, CTRS. FOR DISEASE CONTROL & PREVENTION, http://www.cdc.gov/obesity/causes/index.html (last visited Oct. 21, 2010). 8. Id. 9. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306.

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versa.10 At the same time, no such correlation between income and obesity exists in men.11 Ultimately, the empirical data set forth in this section bears out an important revelation—the intersection of gender and poverty is itself one of the most significant risk factors promoting obesity in American women.

A. Defining Obesity

Though, as previously mentioned, gender is not sufficient in itself to explain the role of gender as an obesity risk factor, the research studies defining and addressing the scope of the obesity problem in America provide an important and necessary backdrop for better understanding the gendered pathology of this disease. As such, the first step in understanding the gender-poverty risk factor posited by this article is crafting a clear definition of “obesity.”

Though capable of multiple constructions, the term “obesity” is uniformly defined in all major sources of empirical data as well as the majority of medical texts. Generally speaking, obesity is the medical condition of maintaining too much body fat.12 Despite its characterization as a disease, obesity is better understood as a “[label] for ranges of weight that are greater than what is generally considered healthy for a given height.”13 Technically, this “label” should be applied anytime an individual’s body mass index (BMI) reaches or exceeds a numerical value of 30.14 Body mass index is calculated by dividing weight (lbs.) by height (in.) squared and multiplying by a factor of 703.15 Any individual—regardless of age, gender, or race—exhibiting a BMI of 30 or more suffers from clinical obesity.

At the same time, “obesity” should not be conflated with the related medical condition “overweight.” Much like obesity, overweight can be understood as another “label” describing a range of weight greater than the healthy weight for a given height. As with obesity, overweight is diagnosed primarily through BMI calculation. In order to be classified as overweight, an individual must present with a BMI between 25 and 29.9.16 Though an important issue meriting its own broad review, the metric of overweight is

10. Youfa Wang & May A. Beydoun, The Obesity Epidemic in the United States—Gender, Age, Socioeconomic, Racial/Ethnic, and Geographic Characteristics: A Systematic Review and Meta-Regression Analysis, 29 EPIDEMIOLOGY REV. 6, 11-12 (2007). 11. Id. 12. Obesity Information, AM. HEART ASS’N, http://www.americanheart.org/ presenter.jhtml?identifier=4639 (last visited Oct. 21, 2010). 13. Overweight and Obesity: Defining Overweight and Obesity, CTRS. FOR DISEASE CONTROL &

PREVENTION, http://www.cdc.gov/nccdphp/dnpa/obesity/defining.htm (last visited Oct. 21, 2010). 14. Id. 15. Id.; see also BMI—Body Mass Index: About BMI Calculator, CTRS. FOR DISEASE CONTROL &

PREVENTION, http://www.cdc.gov/nccdphp/dnpa/bmi/adult_BMI/english_bmi_calculator/bmi_ calculator.htm (last visited Oct. 21, 2010) (providing a program to calculate both English and Metric BMI). 16. CTRS. FOR DISEASE CONTROL & PREVENTION, supra note 13.

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beyond the scope of this Article’s focus on the obesity issue.17 As such, the empirical data that follows excludes information pertaining to overweight and only considers individuals with a BMI of 30 or greater.

One other important connotative concern arises regarding the limits of the obesity definition used by the medical community. Obesity should not be construed as tantamount to “unfitness.” A growing number of scholars have criticized obesity research as creating an inaccurate picture of American health by failing to consider individual variations (e.g., muscle mass) in developing the BMI method.18 While these scholars raise a valid point warranting greater review, the presumption of unfitness may not actually be a definitional problem. Instead, as will be addressed infra in Sections IV.B.2 and IV.B.3, the assumption in the medical community and among laypersons that obesity always amounts to unfitness represents, in many ways, an important repercussion of being a poor, obese woman in America. As such, the standard BMI definition used in the epidemiological tracking of obesity and the vast majority of research addressing obesity in general represents a better, though admittedly not perfect, approach to defining obesity.

B. The Numbers: Who is Currently Obese in America?

The CDC estimated in 2007 that approximately 72 million Americans are obese.19 Similarly, the DHHS reported in 2004 that more than one-third of Americans are obese despite no commensurate increase in the prevalence of overweight-excluding-obesity in forty years.20 Those numbers mark a sharp increase in just four years since the Obesity Society reported that 59 million Americans were obese in 2002.21 Given these startling figures—a significant portion of the population—which Americans are most likely to be obese? This apparently simple question can be answered in two very different ways.

The first, and most straightforward, approach simply isolates individual characteristics like gender, race, socioeconomic status, and age. Though valuable, this overly simplistic evaluative mechanism can only provide isolated snapshots of American obesity relative to the other factors considered by most surveys. As such, this response to the “who is obese” question tends to produce skewed results unfairly attributing obesity to individually tested factors and, in the process, neglecting the complex interplay of even the four narrow factors

17. For more on overweight, its risk factors, and consequences, see Richard Miech et al., Trends in the Association of Poverty with Overweight Among US Adolescents, 1971-2004, 295 JAMA 2385 (2006); Aviva Must et al., The Disease Burden Associated with Overweight and Obesity, 282 JAMA 1523 (1999); Marika Tiggemann & Esther D. Rothblum, Gender Differences in Social Consequences of Perceived Overweight in the United States and Australia, 18 SEX ROLES 75 (1988). 18. PAUL CAMPOS, THE OBESITY MYTH: WHY AMERICA’S OBSESSION WITH WEIGHT IS HAZARDOUS

TO YOUR HEALTH xxii-xxiii (2004); see also GINA KOLATA, RETHINKING THIN, (2007) (reflecting on the lack of individual tailoring attendant to BMI assessments); DEBORAH RHODE, THE BEAUTY BIAS: THE

INJUSTICE OF APPEARANCE IN LIFE AND LAW (2010) (providing an in-depth review of the conflation of appearance and fitness). 19. Ctrs. for Disease Control & Prevention, supra note 2. 20. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 40. 21. U.S. Obesity Trends, THE OBESITY SOC., http://www.obesity.org/statistics/ obesity_trends.asp (last visited Oct. 21, 2010).

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enumerated above. Nonetheless, an analysis of these factors is necessary to understand where single-characteristics cease to have force and, instead, synergistic promotion begins.

In order to comprehend this synergistic promotion, the second, and more sophisticated, approach to predicting which Americans are most likely to become obese requires more than a single-factor answer. Building from the single-factor data, more recent statistical reviews of obesity have begun evaluating various combinations and permutations of gender, race, socioeconomic status, and age to see how factors can combat or contribute to obesity when combined. This multi-factored approach serves to both identify the major causes of obesity and, more importantly, better enable the identification of polices affecting specific populations—a virtually impossible task when looking at any one of these factors in isolation.

1. The Breakdown by Gender, Race, Socioeconomic Status, and Age Starting first with the single-factor approach, several government

organizations and private researchers have developed comprehensive figures addressing gender, race, socioeconomic status, and age. Produced by the government, the DHHS’ biannual publication Health is the primary source for statistical data on obesity and obesity trends. In the private arena, Cynthia Ogden et al.’s “Prevalence of Overweight and Obesity in the United States, 1999-2004” as published in the Journal of the American Medical Association represents the prevailing benchmark against which a significant portion of obesity research is reviewed.22 Despite employing different methodologies, these two major sources of obesity data render very similar figures regarding the correlation between the four characteristics supra and American obesity.

Turning first to gender, women are decidedly more likely than men to develop obesity. By the end of 2004, 34.0 percent of women twenty years of age and older were obese whereas only 30.2 percent of men were obese.23 Following up on these findings, the CDC announced in 2007 that the gender gap had narrowed slightly with 35.3 percent of women and 33.3 percent of men presenting as obese.24 Ogden et al. similarly observed a general obesity rate of 32.2 percent.25 When broken down along gender lines, the Ogden study, which separated obesity and “extreme” obesity defined as a BMI greater than or equal to 40, observed a 2.1 percent increased rate of standard obesity and 4.1 percent increased rate of extreme obesity in women.26 As such, even when isolated, gender consistently produces a readily observable statistical gap.

Turning next to race, only the Ogden study exclusively broke its data down into race-only categories. The study considered three major categories: Caucasian, Black/African American, and Mexican/Latino. Among Caucasians,

22. Ogden, supra note 6. As an example of the importance of this article in the field, the ISI Citation System indicated that more than 492 researchers have relied upon its findings in articles published in various academic journals as of May 2008. 23. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306. 24. Ctrs. for Disease Control & Prevention, supra note 2. 25. Ogden, supra note 6, at 1553 (Table 4). 26. Id. (Table 5).

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the Ogden study found that 30 percent of all adults were classified as obese.27 Among Black/African Americans, that rate rose to 45 percent.28 Among Mexican/Latino individuals, the rate fell between Caucasians and Black/African Americans at 36.8 percent.29 Though the DHHS considered race in conjunction with gender, discussed infra, their figures correlate precisely to the “rank order” produced by the Ogden study with Black/African Americans presenting the highest incidence of obesity followed by Mexican/Latino Americans and Caucasians.30

Examinations of socioeconomic status and obesity rates also produced varying results. The DHHS divided socioeconomic status into three categories: 1) below 100 percent of the poverty level; 2) between 100 percent and 200 percent of the poverty level; and 3) 200 percent or more above the poverty level.31 Broken down in this way, 34.9 percent of individuals presented as “obese” in the first category, 34.6 percent in the second category, and 30.6 percent in the third category.32 The Ogden study did not evaluate its subjects on the basis of socioeconomic status.

Finally, both the DHHS study and the Ogden study tracked the relationship between age and obesity. The DHHS study broke age down into six major categories: 1) 20-34 years; 2) 35-44 years; 3) 45-54 years; 4) 55-64 years; 5) 65-74 years; and 6) 75 years and over.33 The DHHS study found obesity rates of 25.9 percent, 33.5 percent, 34.9 percent, 37.5 percent, 35 percent, and 21.5 percent for each of these categories, respectively.34 The Ogden study broke its findings into only three categories: 1) 20-39 years; 2) 40-59 years; 3) greater than or equal to 60 years.35 The Ogden study found obesity rates of 28.5 percent, 36.8 percent, and 31 percent for each of these categories, respectively.36

Ultimately, while each isolated analysis provides some insight into the factors promoting obesity, no single category provides a conclusive explanation or predictive profile.

2. An Intersectional Review of the Statistics Moving beyond the isolated factor approach discussed supra, both the

DHHS study and the Ogden study also examined the important intersection of gender, race, socioeconomic status, and age to determine how these factors interact to further increase the risk of obesity. For the purposes of this discussion, the most critical of these reviews centers on the combination of gender with each of the three other factors.

27. Id. at 1549. 28. Id. 29. Id. 30. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306. 31. Id. 32. Id. 33. Id. Note that average-by-age statistics in this section are extrapolated from the DHHS male/female-by-age prevalence figures. 34. Id. 35. Ogden, supra note 6, at 1553 (Table 4). 36. Id.

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When looking at the interplay of gender and age, both the DHHS and the Ogden studies observed consistent results among males and females. Generally speaking, the DHHS study’s gender-age figures tracked those listed above with men staying below those rates and women slightly exceeding them. Specifically, the DHHS found that in individuals 20-34 years the obesity rate was 23.2 percent for men and 28.6 percent for women. In the 35-44 age group, the obesity rate was 33.8 percent for men and 33.3 percent for women.37 In the 45-54 age group, the obesity rate was 31.8 percent for men and 38 percent for women. In the 55-64 age group, the obesity rate was 36 percent for men and 39 percent for women. In the 65-74 age group, the obesity rate was 32.1 percent for men and 37.9 percent for women. Finally, in the 75 and over age group, the obesity rate dropped to 19.9 percent for men and 23.2 percent for women.38 In total, the average age disparity between men and women by age was 3.9 percent—closely adhering to the observed rate differences in men and women generally. These findings are also generally supported by the Ogden study, which looked at only three major age groups. In the 20-39 age group, the obesity rate was 28 percent for men and 28.9 percent for women. In the 40-59 age group, the obesity rate was 34.8 percent for men and 38.8 percent for women. Finally in the 60 and over age group, the obesity rate was 30.4 percent for men and 31.5 percent for women.39 In total, the Ogden study observed an average age disparity of 2 percent—only 0.1 percent lower than its reported gender gap. Ultimately, then, both studies suggest that age similarly affects obesity rates in both men and women.

Turning next to gender and race, the most interesting aspect of the DHHS and Ogden data may be the consistency of male obesity rates across races compared to the inconsistency among females of different race groups. Both studies grouped individuals as Caucasians, Black/African Americans, and Mexican/Latinos. In males, the Ogden study found an obesity rate of 31.1 percent among Caucasians, 34 percent among Black/African Americans, and 31.6 percent among Mexican/Latinos.40 Similarly the DHHS study observed generally consistent figures between race groups. The DHHS found that 31 percent of Caucasian men, 31.2 percent of Black/African American men, and 30.5 percent of Mexican/Latino men were obese.41 Despite the parity among men, the congruent rates along race lines terminate when female obesity rates are considered. The Ogden study found that 30.2 percent of Caucasian women, 53.9 percent of Black/African American women, and 42.3 percent of Mexican/Latino women were obese.42 Similarly, the DHHS found female rates of obesity were at 31.5 percent for Caucasians, 51.6 percent for Black/African

37. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306. Notably, as demonstrated by the figures infra, the “35-44” age group was the only category in which women presented at a lower rate than men. 38. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306. 39. Ogden, supra note 6, at 1553 (Table 4). 40. Id. at 1554 (Table 5). 41. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306. 42. Ogden, supra note 6, at 1553 (Table 5).

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Americans, and 40.3 percent for Mexican/Latinos.43 Consequently, the correlation between race and obesity appears to adhere only in female subjects.

Finally, the intersection of gender and poverty provides some of the most surprising data. Though neither the DHHS study nor the Ogden study analyzed poverty along gender lines, two recent publications have broken down the data to focus specifically on the correlation between gender and poverty. First, Adam Drewnowski and S.E. Specter recently reviewed the 2004 aggregate obesity statistics and tracked the correlation between obesity, percent of the poverty level of obese individuals, gender, and years of education of obese individuals.44 Regarding poverty level, they considered four socioeconomic classifications: 1) less than 100 percent of the poverty level; 2) between 100 and 199 percent of the poverty level; 3) between 200 and 399 percent of the poverty level; and 4) greater than 400 percent of the poverty level.45 In the first category, Drewnowski and Specter observed a nearly 16 percent disparity between men and women. In the second category, that disparity dropped to approximately 5 percent followed by 1 percent in the third category. In the final category, women actually presented less frequently than men with an average obesity rate of only 13 percent. More strikingly, while men’s obesity rose with socioeconomic status until men entered the 200-399 percent poverty range, women’s rates of obesity consistently declined with increased income.46

Drewnowski and Specter are not alone in these findings. A 2007 study by Youfa Wang and May Beydoun appears to confirm these figures.47 Relying upon three general socioeconomic categories, Wang and Beydoun found that men of low socioeconomic status presented as obese 26.7 percent of the time, men of medium socioeconomic status presented as obese 29.4 percent of the time, and men of high socioeconomic status presented as obese 23.6 percent of the time—exactly mirroring the brief rise and fall observed by Drewnowski and Specter.48 At the same time, Wang and Beydoun observed rates of 37.8 percent obesity in low socioeconomic status women, 34.5 percent obesity in middle socioeconomic status women, and 29.9 percent in high socioeconomic status women—again matching the steady decline observed by Drewnowski and Specter.49

Analyzing socioeconomic status in terms of education, Drewnowski and Specter broke the data into five categories: 1) less than 12 years of education; 2) 12 years of education; 3) 12-16 years of education; 4) 16 years of education; and 5) more than 16 years of education.50 Among women with less than 12 years of education, the obesity rate was 27.5 percent—5.5 percent higher than that observed in similarly situated men. For women with 12 years of education or

43. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306. 44. Adam Drewnowski & S.E. Specter, Poverty and Obesity: The Role of Energy Density and Energy Costs, 79 AM. J. CLINICAL NUTRITION 6 (2004). 45. Id. at 7. 46. Id. 47. Wang & Beydoun, supra note 10. 48. Id. at 13. 49. Id. 50. Drewnowski & Specter, supra note 44, at 7.

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more, however, women were consistently less likely to be obese than their male counterparts in every category. While this trend of decreased obesity with increased education holds for men as well, women’s obesity rates dropped 16 percent between the first and final categories whereas men’s rates only dropped 10 percent.51 In total, both the Drewnowski and Specter review as well as the Wang-Beydoun study clearly indicate a direct correlation between poverty and obesity unique to women.

C. The Trends: A Dynamic Picture of American Obesity

One final empirical consideration bears review before turning to the implications of this data. While all of the factual information set forth supra provides a concise and accurate snapshot of obesity in America at a particular moment, the broader obesity trends tracked by the DHHS also demand at least a cursory glance before proceeding. The DHHS began collecting obesity data with the first National Health and Nutritional Examination Survey (NHANES) in 1956.52 Since that time, NHANES has included information relating to the prevalence of healthy weight, overweight, and obesity among Americans as collected on five discrete occasions at various time intervals ranging from two years up to eight years.

The DHHS, through NHANES, has consistently tracked both aggregate obesity figures and obesity-by-gender figures in all five studies. The five periods of study for these two categories of obesity data were: 1) 1960-1962; 2) 1971-1974; 3) 1976-1980; 4) 1988-1994; and 5) 2001-2004.53 For these periods, the DHHS observed an initial gradual rise in obesity prevalence followed by a sharp increase in the 1990s and early 2000s. Specifically, rates only climbed from 13.3 percent in 1960-1962 to 14.6 percent in 1971-1974, and then to 15.1 percent in 1976-1980.54 Thereafter, obesity increased at a much faster pace with an observed rate of 23.3 in 1988-1994 and, finally, 32.1 percent in 2002.55

The gender-obesity gap has traveled along a similar path generally maintaining a 4 to 6 percent disparity. In 1960-1962, women presented at a rate 5.7 percent greater than men. In 1971-1974, women presented at a rate 4.6 percent greater than men. In 1976-1980, that number declined slightly to 4.3 percent only to rebound to 5.4 percent in 1988-1994. In 2001-2004, the gap narrowed to its lowest level in any recorded period to settle at 3.8 percent.56

Poverty level tracking did not begin until the 1971-1974 study. In that first study, individuals below the poverty level had an obesity rate of 20.7 percent, whereas those between 100 and 200 percent of poverty only presented as obese 18.4 percent of the time and those above 200 percent were obese only 12.4 percent of the time. These figures remained almost unchanged in 1976-1980 with figures of 21.9 percent, 18.7 percent, and 12.9 percent, respectively. In the

51. Id. 52. About the National Health and Nutrition Examination Survey, CTRS. FOR DISEASE CONTROL &

PREVENTION, http://www.cdc.gov/nchs/nhanes/about_nhanes.htm (last visited Oct. 21, 2010). 53. NAT’L CTR. FOR HEALTH STATISTICS, supra note 3, at 306. 54. Id. 55. Id. 56. Id.

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1988-1994 study, these percentages increased to 29.2 percent, 26.6 percent, and 21.4 percent but remained in the same rank order. Only in the 2001-2004 study did the rank order come close to changing as the gap between the first two categories became almost equal. Consequently, while narrowed, the general poverty observations have remained constant throughout the more than forty-year period.57

Finally, race tracking was only employed in the final three studies. Among Caucasians, obesity rose from 12.4 percent in males and 15.4 percent in females in 1976-1980 to 31 percent in males and 31.5 percent in females in 2001-2004. Among Black/African Americans, obesity rose from 16.5 percent in males and 31 percent in females in 1976-1980 to 31.2 percent in males and 51.6 percent in females in 2001-2004. Finally, in Mexican/Latinos, obesity rose from 15.7 percent in males and 26.6 percent in females in 1976-1980 to 30.5 percent in males and 40.3 percent in females in 2001-2004. As such, general distribution of obesity among race groups, while increased overall, has generally remained constant.58

In short, every trend line tracking obesity in the five NHANES studies shows dramatic increases in obesity generally consistent along lines of poverty, race, and gender.

D. Conclusions Derived From This Data

After exhaustively reviewing the data compiled by the DHHS, the NHANES studies, and various independent scholars, the data on American obesity renders four important observations. First, whatever is causing increased obesity in women is not new. Second, something about race is driving increased obesity but it generally only affects the women within these minority groups. Third, poverty only has a significant impact on obesity rates for women. And, finally, consideration of any of these factors in isolation obscures the motivating synergy driving the heightened obesity observed in women.

As the longitudinal studies indicate, women have consistently been more obese than men since data collection began. While the margin of difference may vary from year to year, the consistent 4 to 6 percent disparity observed in every NHANES study suggests an important point: some constant factor likely drives the different prevalence in women and men. Considering the relatively miniscule effect of biological disorders on the obesity rates, that factor likely is social. Even with the recent narrowing of the gender gap observed by the CDC, the persistence of a distinction between men and women’s obesity rates further suggests a common social factor may be driving the disparity.

In the same way that some unidentified social factor appears to be driving obesity in women versus men, some unidentified social factor appears to be driving obesity disparities between the three surveyed racial groupings. Yet once these groupings are broken down by gender, a very different image emerges. Rather than seeing consistent rates of obesity among women of different races, we see heightened obesity for women in all groups, with some

57. Id. 58. Id.

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factor further exacerbating obesity rates in minority women. As argued in more detail infra, this overlap in gender disparity combined with the heightened impact on certain racial groups suggests that whatever unidentified factor drives the gender disparity has a bigger impact on and/or is more pervasive among minority women than Caucasian women.

What is that factor? Poverty. Considering the gender data first, Drewnowski and Specter as well as Wang and Beydoun, both demonstrate a direct correlation between poverty and obesity in women. These studies show that women living in poverty are significantly more likely to be obese than men living in poverty, the risk attached to poverty decreases with movement up the socioeconomic ladder, and men do not experience the same dramatic decline in obesity as observed in women. In short, poverty alone seems to have a unique and important influence on which American women will become obese. Yet this uni-factor analysis of women’s obesity still obscures the critical role of poverty and social welfare programs in promoting American obesity.

In isolating poverty as the source of increased obesity in women, the intersections of this data begs reiteration to identify at least one probable source of heightened obesity in women with limited economic resources. In the uni-factor setting, women are more likely than men to be obese; women of color are more likely to be obese than Caucasian women; poor women are more likely to be obese than wealthy women. When these factors are combined, the disparities in the data begin to align. Women of color are more than twice as likely as Caucasian women to live at or below the poverty level.59 What is more, women in poverty are generally more likely to partake in the social welfare programs discussed infra. Specifically, food stamps are provided to 4.5 million more women than men, and 21 million women as opposed to 16 million men are eligible to partake in the food stamps program.60 Similarly, women are more likely to participate in TANF, and TANF participants are twice as likely to participate in the food stamps program.61 As such, what seems to unify obese women in America into a single group is poverty, and one consequence of that poverty is a shared experience in the American social welfare system. Building from this empirical analysis, then, the question becomes: is America’s social welfare infrastructures making women obese? The answer is yes.

III. A LOOK AT THE PUBLIC POLICIES DRIVING FEMALE OBESITY

Building off of the empirical data suggesting that the source of increased female obesity is largely the common social experience created by social welfare programs, the next question is which policies are driving this persistent socioeconomic gender gap. In particular, this Section will examine the two most significant and readily apparent programs driving this problem. First, it will explore the ways in which the Food Stamps program fails to provide access to

59. U.S. CENSUS BUREAU, ANNUAL SOCIAL AND ECONOMIC SUPPLEMENT: AGE AND SEX OF ALL

PEOPLE, FAMILY MEMBERS AND UNRELATED INDIVIDUALS ITERATED BY INCOME-TO-POVERTY RATIO

AND RACE: BELOW 100% OF POVERTY, ALL RACES (2005), available at http://pubdb3.census.gov/ macro/032005/pov/new01_100_01.htm (Table POV01). 60. U.S. DEP’T OF AGRIC., Trends in Food Stamp Program Participation Rates: 1999 to 2005 (2006). 61. Id. at 7 n.9.

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healthy foods while actually promoting over-consumption. Second, it will consider the negative impact of the TANF program on food security and the availability of non-employment time for activities such as meal preparation and exercise. A. Food Stamps: Problems of Security and Access

The Supplemental Nutrition Assistance Program (SNAP) has served as the

primary universal nutrition safety net provided by the federal government since 1939. In the nearly 70 years since its inception, SNAP has transformed through congressional legislation from a simple surplus purchase program into an intricate social entitlement program providing assistance to more than 30 million individuals.62 For almost the entirety of its existence, the primary goal of the United States Department of Agriculture (USDA), the program’s primary federal administrative body, has been to expand the reach of the program to make more Americans eligible, remove barriers to participation, and increase enrollment among eligible groups.63

Despite enormous success in these efforts to expand, scholars examining SNAP have only recently begun to ask whether food stamps may actually be harming enrolled individuals.64 Though these concerns about how food stamps incentivize certain types of behavior take a variety of forms, two particular concerns take center stage in the ongoing obesity discussion. First, though food stamps have become increasingly easy to use in recent years, improved efficiency has not been effectively paired with efforts to make healthy food choices more accessible.65 Second, the inadequacy of monthly benefits, the long cyclical period of distribution, and general participant instability renders participation in the program more difficult and less certain. This trio of problems promotes one of the greatest impetuses driving over-consumption—food insecurity. Combined, limited access to healthy foods under SNAP and heightened food insecurity may explain the correlation between SNAP participation and obesity—particularly in women.66

1. Understanding the Workings and Evolution of the Modern SNAP Before examining the two narrow problems undermining the value of

SNAP and promoting obesity in women, it is important to first understand how

62. A Short History of SNAP, U.S. DEP’T OF AGRIC., http://www.fns.usda.gov/SNAP/ rules/Legislation/about.htm (last visited Jan. 31, 2010). 63. Id. 64. See generally Adam Benforado et al., Broken Scales: Obesity and Justice in America, 53 EMORY

L.J. 1645 (2004) (linking food stamp participation to marriage failure and long-term dependence on government benefits, in addition to overweight and obesity); Tracy Hampton, Food Insecurity Harms Health, Well-being of Millions in the United States 298 JAMA 1851 (2007) (assessing the link between SNAP and food insecurity as a potential health risk). 65. See, e.g., Deja Hendrickson et al., Fruit and Vegetable Access in Four Low-Income Food Desert Communities in Minnesota, 23 AGRIC. AND HUM. VALUES 371, 372 (2006). 66. As discussed in greater detail infra, this conclusion should not be construed as suggesting that entitlement programs should be terminated or made more exclusive. Rather, it reflects only on the problems created by the mechanics of social welfare participation under the current regime.

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the modern SNAP functions on a daily basis and how that function has changed since the inception of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA). This brief review will both explain questions of eligibility and the practical difficulties attendant to actually making use of the food aid benefits afforded by SNAP.

First, on the matter of eligibility, several qualifications govern participation. The foremost requirement is citizenship or qualifying legal status.67 As a consequence, all undocumented individuals residing in the United States are categorically excluded from SNAP aid. In addition, the list of qualifying non-citizens is narrowly constrained to reach only certain groups.68 While legal immigrant children and Lawful Permanent Residents (LPRs) with military connections are immediately eligible, all other non-disabled adult legal immigrants must first qualify for LPR status then accrue a 40-credit work history to gain eligibility status.69 Second, an able-bodied individual between the ages of 18 and 60 must engage in a certain amount of work activity in order to receive benefits.70 Initially introduced as part of a series of changes in the 1970s, the work requirement acquired new teeth with the enactment of PRWORA when SNAP time limits were formally linked to work performance.71 Finally, eligibility only extends to households with a maximum income of $2,000 per month exclusive of TANF income and Supplemental Security Income (SSI).72 For households including disabled persons, the cap rises to $3,000 per month.73

Beyond eligibility, the other piece of information critical to assessing the impact of SNAP is the manner in which it actually allows the consumption of benefits. SNAP functions as a block grant program whereby, generally, states are responsible for certification of participants and issuance of aid, while the federal government bears responsibility for funding awarded benefits and authorizing retailer participation.74 While SNAP at one time used stamps that were redeemed in place of cash, all SNAP participants throughout the United States now employ territory-wide Electronic Benefits Transfer (EBT) to spend awarded benefits. EBT benefits are distributed and utilized in the form of a card resembling an ATM card. An EBT card may be charged for permitted purchases of food products like a regular ATM or credit card at the checkout stand of participating retailers.75

Once a participant qualifies and receives their EBT card, the primary question that remains is where the benefits may be spent. Generally, a retailer will qualify to participate in SNAP if they offer for sale, on a continuous basis, at least three varieties of qualifying: a) meat, poultry or fish; b) bread or cereal; c)

67. SOC. SECURITY ADMIN., PUB. 05-10100, FOOD STAMPS AND OTHER NUTRITION PROGRAMS 2-3 (2007), available at http://www.ssa.gov/pubs/10100.pdf. 68. Id. 69. Id. 70. Id. 71. U.S. DEP’T OF AGRIC., supra note 60. 72. SOC. SECURITY ADMIN., supra note 67, at 4. 73. Id. 74. Id. 75. Id.

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vegetables or fruits; and d) dairy products.76 Alternatively, retailers who earn more than half of the total dollar amount of all sales in the form of eligible food staples also qualify.77 Once a retailer qualifies under the federal guidelines, the retailer may accept EBT cards from any participant.

2. Impossible Choices: Addressing Limited Access to Healthy Foods The first major problem driving obesity among SNAP participants—a

group largely made up of poor women—stems from the contradiction between advised purchases and real world market conditions. While the Farm Bill of 2002 introduced new funding to instruct participants on proper nutrition, no accompanying provision promoting access to those healthy foods suggested by the nutritional materials was ever even considered.78 Instead, Congress has and continues to proceed on the presumption that all Americans have easy access to a participating supermarket where they can purchase the “right” foods.

According to the USDA, the following classes of products are available for purchase with an individual’s monthly allotment of food stamps: breads and cereals, fruits and vegetables, meats, fish and poultry, and dairy products as well as seeds or plants that will produce food.79 At the same time, the SNAP forbids the use of food stamps to purchase alcohol, tobacco, nonfood items like paper products and pet food, vitamins and medicines, food eaten in the store, and hot foods.80 Though this list suggests participants gain access to a balance of healthy foods, what happens when the only accepting provider is a small corner store stocking only high fat meats, whole milk, high calorie breads and cereals, and, possibly, no produce? This situation is not as farfetched as it may seem. Large portions of poor urban and rural residents live in so-called “food deserts.” A “food desert” refers to an area with severely limited access to consumer food sources.81

In these food deserts, individuals are often forced to make difficult consumptive choices. In areas where only convenience stores, with their very limited selection of healthy foods, are readily accessible, individuals tend to chose among unhealthy options rather than undertake the often difficult task of coordinating childcare and transportation to reach (and perhaps more problematically bring large amounts of groceries back from) supermarkets outside their neighborhoods.82 In a study of four Minneapolis food deserts,83

76. Supplemental Nutrition Assistance Program: Store Eligibility Requirements, U.S. DEP’T OF AGRIC., http://www.fns.usda.gov/snap/retailers/store-eligibility.htm SNAP (last visited Oct. 21, 2010). 77. Id. 78. U.S. DEP’T OF AGRIC., supra note 60. 79. Supplemental Nutrition Assistance Program: Frequently Asked Questions, U.S. DEP’T OF AGRIC., http://www.fns.usda.gov/snap/faqs.htm (last visited Oct. 21, 2010). 80. Id. 81. Deja Hendrickson et al., supra note 65, at 372. 82. Id. at 381; see also J. Pearce et al., The Contextual Effects of Neighborhood Access to Supermarkets and Convenience Stores on Individual Fruit and Vegetable Consumption 62 J. OF EPIDEMIOLOGY &

COMMUNITY HEALTH 198 (2008) (noting that this holds true even where empirical data revealed similar fruit and vegetable consumption in food deserts). 83. Hendrickson et al., supra note 65, at 372. Researchers in this study defined “food deserts” as “urban areas with 10 or fewer stores and no stores with more than 20 employees.”

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researchers found that prices within the surveyed area were markedly higher than at major retail chains outside the selected area and basic healthy foods like apples and broccoli were virtually unavailable.84 This phenomenon is not limited, however to Minneapolis. Food deserts exist in New York City,85 Chicago,86 the San Francisco Bay area,87 and other major metropolitan and rural areas.88 Additionally, these deserts consistently arise only in areas of significant poverty—limiting their impact to those most likely to be constrained in their purchasing power and reliant upon SNAP benefits to purchase food—impoverished women.89

Though overlooked by the USDA, these food deserts encompassing a large number of poor communities represent a major problem in the battle against obesity. In short, food deserts erect high barriers between SNAP benefits and healthy food choices—virtually insurmountable barriers for women forced to secure childcare, forgo wages, and either make use of time-consuming public transportation or procure other means of reaching supermarkets to get access to healthy foods. This impacts obesity rates because individuals subject to these pressures will simply elect the more expedient option of walking to the corner store and purchasing processed food, whole milk, and high calorie breads in place of much needed fruits and vegetables.90 In a nationally representative sample of low-income households, a recent study discovered that easy access to supermarkets offering a broad array of choices increased household consumption of fruits and vegetables by roughly 84 grams per day among SNAP participants.91 Yet, at the same time, 25 percent of SNAP participants lacked “easy access” to a supermarket and the attendant healthy eating benefits.92

Limited access to supermarkets and ready access to convenience stores not only correlates to fruit and vegetable consumption but, more importantly, directly correlates to obesity. In a 2006 study, researchers discovered that relative proximity to a supermarket reduced the prevalence of obesity by an obesity prevalence ratio of 0.83, whereas relative proximity to convenience stores in place of supermarkets (with their limited healthy choice options)

84. Id. at 375. 85. Editorial, A Streetcart Named Healthy, N.Y. TIMES, Mar. 1, 2008, http://www.nytimes.com/ 2008/03/01/opinion/01sat4.html. 86. Monica Eng, 3 New Farmers Markets to Bring Fresh Produce to Areas with No Big Grocery Stores, CHI. TRIB., Mar. 29, 2008, at C1 available at http://articles.chicagotribune.com/2008-03-29/news/0803290109_1_farmers-markets-prepared-food-vendors-grocery. 87. Veronica Sudekum, An Oasis in a Food Desert, PALO ALTO WKLY., Apr. 16, 2008, available at http://www.collectiveroots.org/oasis_food_desert. 88. See Fresh & Easy, and Missing, L.A. TIMES, Nov. 17, 2007, at A20; Diana Suchetka, Clinic’s Farmers Market Hailed as a Fresh Idea, PLAIN DEALER (Cleveland), Apr. 23, 2008, at B1; Sarah Fritschner, Dirt and Democracy, THE COURIER-JOURNAL (Louisville), Feb. 13, 2008, at 1E. 89. See generally Elizabeth A. Baker et al., Peer Reviewed: The Role of Race and Poverty in Access to Foods That Enable Individuals to Adhere to Dietary Guidelines, 3 PREVENTING CHRONIC DISEASE, no. 3, July, 2006, at 1. 90. Hendrickson et al., supra note 65, at 381. 91. Donald Rose & Rickelle Richards, Food Store Access and Household Fruit and Vegetable Use Among Participants in the US Food Stamp Program, 7 PUB. HEALTH NUTRITION 1081, 1081 (2004). 92. Id. at 1085.

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produced a high obesity prevalence ratio of 1.16. Ultimately, educational support on healthy choices fails to play a causal role in increasing fruit and vegetable consumption when divorced from the reality of limited supermarket access.93

Consequently, this array of empirical research on the importance of access—not simply benefits—suggests the USDA efforts to cultivate a healthy SNAP program are failing. Educating participants on what choices to make cannot decrease obesity rates among participants if they have no opportunity to make those choices. The majority of food stamp participants reside in food deserts and more than 25 percent cannot reach and return from a supermarket within the thirty-minute94 window necessary to encourage use of supermarkets over closer convenience stores.95 As such, even when participants are left with ample benefits, they have nothing healthy to spend them on—leading to almost exclusive consumption of high calorie foods in place of healthier choices.

3. A Formula for Obesity: Limited Choices + Instability At the same time that SNAP encourages selection of bad choices, the

general instability imposed by limitations on SNAP benefits creates new incentives to over-consume by creating widespread food insecurity among participants. Food insecurity is best defined as “limited or uncertain availability of nutritionally adequate and safe foods or limited or uncertain ability to acquire acceptable foods in socially acceptable ways.”96 As early as 1998, the USDA recognized the correlation between heightened food stamp usage and increased food insecurity.97 Problematically, though, the USDA refuses to recognize the important connection between food insecurity and obesity.98

How does food insecurity interact with obesity? Simply put, food insecurity promotes obesity by encouraging over consumption in anticipation of future caloric shortfalls. This problem is then exacerbated by the availability of low-cost, high-calorie, high-fat foods more readily affordable on the meager benefits provided by the current SNAP.99 These behaviors, and the corresponding weight consequence, are particularly prevalent among women. In one study focusing on overweight individuals, researchers discovered that women reporting even brief periods of mild food insecurity presented as overweight at a rate 30 percent higher than that observed in women reporting

93. Kimberly Morland et al., Supermarkets, Other Food Stores, and Obesity: The Atherosclerosis Risk in Communities Study, 30 AM. J. PREVENTIVE MED. 333 (2006). 94. Rose & Rickards, supra note 91, at 1085. The thirty-minute window refers only to travel time, not shopping time. 95. Id. 96. MARK NORD ET AL., U.S. DEP’T OF AGRIC., FOOD ASSISTANCE & NUTRITION RESEARCH, PREVALENCE OF FOOD INSECURITY AND HUNGER BY STATE, 1996-1998 (1999), at 2 available at http://www.ers.usda.gov/publications/fanrr2/fanrr2.pdf. 97. Id. at 10. 98. See Michele Ver Ploeg et al., U.S. Dep’t. of Agric., Econ. Research Serv., Food Stamps and Obesity: Ironic Twist or Complex Puzzle? AMBER WAVES, Feb. 2006. 99. Hampton, supra note 64, at 1851.

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no experiences of food insecurity.100 As ironic as this finding appears at first, the threat of hunger and undernourishment actually promotes obesity in poor women. When the need to draw upon the fat reserves created in anticipation of hunger never arises, however, the stored calories are not used and the unhealthy weight gain remains.

This problem of food insecurity, though, may seem at first glance beyond the reach of SNAP. After all, SNAP does not mandate a specific grocery list and it is supposedly calculated to allow participating individuals to adequately acquire sufficient nutrition. Yet, such an understanding of food stamps neglects two important factors. First, the current manifestations of SNAP simply do not provide sufficient resources to permit easy and, perhaps more importantly, secure subsistence. Second, combined with the problem of limited access discussed supra, insecurity encourages participants to exhaust their monthly benefits on some of the least healthy choices possible.

The benefits afforded to SNAP participants depend on a variety of factors including household income, rent or mortgage costs, and medical expenses.101 In general, though, the average food stamp benefit amounts to the equivalent of roughly $21 per week per person.102 What’s more, food stamps are only provided on a monthly basis. Some scholars suggest that this extended budgeting period creates food insecurity in its own right by interjecting such an extensive period between benefits payments.103 Nationally, citizens have called upon their elected representatives to undertake the Food Stamp Challenge.104 Those responding to the call have consistently reported back their new found recognition of the exceptional difficulty of securing enough healthy food on a mere $3 per day.105 While the challenge has done an excellent job raising awareness of hunger, it has failed to bring about commensurate change. Instead, most SNAP participants are left purchasing what $3 per day can buy.

The second problem tied to food security stemming from the current SNAP administrative procedures relates to how excess benefits are treated. Where limited benefits encourage food insecurity, the response among participants will almost uniformly be to use all food stamp benefits even where not necessary in a given week.106 Unable to reach a supermarket, participants will spend all of those remaining benefits on the poor choices at nearby convenience stores.107 This behavioral response promoted by the food insecurity permeating SNAP

100. Marilyn S. Townsend et al., Food Insecurity is Positively Related to Overweight in Women, 131 J. NUTRITION 1738, 1738 (2001). 101. SOC. SECURITY ADMIN., supra note 67. 102. Jessica Brown, Food Stamp Menu Hard to Follow for a Week, CINCINNATI ENQUIRER, Nov. 12, 2007, at 1B. 103. Parke E. Wilde & Jerusha N. Peterman, Individual Weight Change is Associated with Household Food Security Status, 136 J. NUTRITION 1395, 1399 (2006). 104. See William Yardley, A Governor Truly Tightens His Belt, N.Y. TIMES, May 1, 2007, at A14. 105. Id.; see also Jessica Fargen, Mayor Takes Food Stamp Challenge to Fill His Belly on $21 per Week, BOSTON HERALD, Oct. 23, 2007, at 3; Barb Galbincea, Could You Live on $21 A Week For Food? PLAIN

DEALER(Cleveland), Oct. 4, 2007, at B1. 106. Hampton, supra note 64, at 1851-52. 107. See Hendrickson et al., supra note 65, at 381; Pearce, supra note 82, at 200.

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participation provides at least one strong explanation of the heightened obesity observed in participants.

Combining the limited accessibility problem with food insecurity consistently produces the same results—over-consumption of unhealthy foods creating a caloric imbalance leading to obesity. Because poor women are more likely to participate in SNAP and face the logistical difficulties associated with reaching healthy choices under the program, they are often faced with a distressing choice—meeting their basic necessity or properly addressing the long-term health consequences of poor eating habits.

B. TANF: Another Cost of TANF Welfare-to-Work Requirements

In 1996, PRWORA officially ended the 40-year run of the federally administered Aid to Families with Dependent Children (AFDC) program and replaced this critical social safety net with a state-run, federally funded block grant program entitled Temporary Aid to Needy Families (TANF).108 The dramatic PRWORA legislative package was hailed as “the end to welfare as we know it” in then-President Bill Clinton’s 1993 State of the Union Address.109 This devolution of federal authority and responsibility on the states did far more than unburden the federal government of responsibility for providing a social safety net. Instead, Congress imposed an array of conditions, requirements, and new limitations upon would-be TANF recipients never before seen in the AFDC regime.

For the purposes of this conversation, two of PRWORA’s TANF funding conditions take on particular importance. First, PRWORA created a lifetime limit on TANF eligibility. Specifically, that statute limited benefit payments to a maximum of 5 years for an individual participant.110 Second, PRWORA mandated that all adult recipients of TANF benefits engage in at least 20 hours of “work activity” per week during any month in which benefits are received, with that number gradually climbing to 30 hours per week of “work activity” in 2000.111

These changes stripped TANF benefits of entitlement status and created two critical problems affecting the rise of obesity in the years that followed. The end of entitlement status and the introduction of the new requirements potentially leading to unstable program participation created in participants a heightened sense of food insecurity—bringing with it all of the problems attached thereto discussed supra in relation to food stamps.112 Additionally, in a

108. AVIS JONES-DEWEEVER ET AL., INST. FOR WOMEN’S POL’Y RESEARCH, BEFORE AND AFTER

WELFARE REFORM: THE WORK AND WELL-BEING OF LOW-INCOME SINGLE PARENT FAMILIES 1 (2003); see generally Welfare to Work, 7(1) FUTURE CHILD. 1 (1997) (Providing an exhaustive discussion of the AFDC-to-TANF reform movement, this volume addresses “Welfare to Work” and contains articles addressing many well-known and not-so-well-known facets of the welfare reform debate). 109. Address Before a Joint Session of Congress on Administration Goals, 1 PUB. PAPERS 113, 117

(Feb. 17, 1993). 110. 42 U.S.C. § 608 (2006). 111. 42 U.S.C. § 607 (2006). 112. See DAN LEWIS, ILL. FAMS. STUDY, POL’Y BRIEF NO. 8, PUTTING FOOD ON THE TABLE AFTER

WELFARE REFORM: WHAT PROTECTS FAMILIES FROM FOOD INSECURITY? 3 (2002).

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social context where women already devote more hours to family care responsibility, the imposition of work requirements, albeit reduced to 20 hours, likely curtails the ability of female participants to make time for essential health-promoting activities like trekking to supermarkets rather than nearby convenience stores, preparing meals, and engaging in fitness activities. Combined, these two factors suggest that PRWORA’s “personal responsibility” measures may actually be forcing women to choose between the extremes of subsistence and obesity.

1. The Impact of TANF on Food Security The problem of food insecurity created by the flaws in SNAP are only exacerbated by the additional welfare participation requirements imposed upon TANF participants following the enactment of PRWORA. While not all SNAP participants enroll in TANF or vice versa, TANF participants are twice as likely to enroll in SNAP than eligible non-TANF participants113—suggesting that TANF participants are more likely than other poor individuals to be subject to the differing but rigorous requirements of each program. Considering empirical research has already demonstrated that the more lax work requirements of SNAP increase food insecurity, TANF’s more demanding 30-hour workweek and sharp limits on benefits likely exacerbate the prevalence of food insecurity.114

Poverty is the greatest predictor of food insecurity. The problem with food insecurity stems from a combination of actual food insufficiency as well as the ever-present pressures of household and budgetary management, for a group of individuals typically possessing only limited education and fiscal know-how.115 In a review of post-TANF food insecurity among single mothers, 36 percent of post-TANF single-mothers experienced some form of material hardship including: sometimes not having enough food, being evicted, being homeless, or having utilities cut off.116 The same researchers found, though, that income in no way correlated to either food insufficiency or food insecurity-inducing material hardship. What does this mean? At least one DHHS report explains the problem as follows: “The level of hardship documented among the post-TANF leavers, even among those with steady employment, suggests that leaving welfare does not translate into a higher level of well-being.”117 Consequently, in a system premised on and constantly incentivizing reduced

113. U.S. DEPT. OF AGRIC., TRENDS IN FOOD STAMP PROGRAM PARTICIPATION RATES: 1999 TO 2005, at 7 n.9 (2007). 114. Helen Jensen, Food Insecurity and the Food Stamp Program, 84 AM. J. AGRIC. ECON. 1215, 1225 (2002). 115. See Mary E. Corcoran et al., Food Insufficiency and Material Hardship in Post-TANF Welfare Families, 60 OHIO ST. L.J. 1395, 1399-1400 (1999); see also Katherine Alaimo et al., Food Insufficiency Exists in the United States: Results from the Third National Health and Nutrition Examination Survey, 88 AM. J. PUB. HEALTH 419 (1998). 116. Corcoran, supra note 115, at 1408. 117. NANDITA VERMA ET AL., MONITORING OUTCOMES FOR CUYAHOGA COUNTY’S WELFARE

LEAVERS: HOW ARE THEY FARING? 11 (2001).

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caseloads,118 individual participants are being exposed to greater food insecurity as a direct consequence of TANF’s “purge the rolls” philosophy.

This problem of TANF-enhanced food insecurity is particularly forceful among women. Factors such as physical and mental health problems, domestic abuse, and lack of access to transportation positively correlate to increased reports of insecurity and experiences of material hardship.119 These problems—a cause for food insecurity and, by extension over-consumption-producing obesity—disproportionately affect female recipients of aid. This disproportionate effect is even greater among the largest group of program subscribers—women of color.120 Viewed in this way, the obesity disparities observed between women of different races appears to correlate not with cultural differences but with differences in social welfare program participation. Ultimately, while TANF participation may not be the only predictor of obesity in poor women, the failure of the TANF administrators to recognize the added pressures driving food insecurity among single mother participants appears to account for at least a portion of the disparity.

2. TANF and Women’s Limited Temporal Capital In addition to promoting food insecurity and its attendant problems, TANF

can also be linked to a reduction in the amount of temporal capital121 available for travel in order to secure healthy foods, engage in preparation of healthy meals, and exercise. While TANF certainly impacts the temporal capital of all participants, the impact on women is especially significant given that women already incur added responsibilities absorbing much of their free time when engaged in work outside the home. Though not yet empirically reviewed, the complex interaction between TANF’s time-consuming demands and the special added responsibilities likely dramatically increases “time poverty”122 and forces poor women to choose between satisfying TANF and pursuing a healthy diet.

The stresses and restrictions imposed on American women’s time almost universally exceed those imposed upon American men’s time. A recent University of Michigan study found that women still bear responsibility for approximately 17 hours per week of household chores while their male counterparts only perform 13 hours per week.123 Though the Michigan study only considered women versus men, other reviews have examined the impact of actual wage earnings on female housework hours. The only factor empirically

118. See Matthew Diller, The Revolution in Welfare Administration: Rules, Discretion, and Entrepreneurial Government, 75 N.Y.U. L. REV. 1121 (2000) (exploring the development of the caseload centric administrative approach developed in response to PRWORA). 119. Corcoran, supra note 115, at 1403. 120. Id. at 1408-09, 1413. 121. “Temporal capital” should be understood as the amount of time available to engage in both work and non-work activities. 122. Though defined in a variety of ways by practitioners applying the concept to other fields, “time poverty” in this context is best understood as referring to the lack of sufficient time to meet the required time expenditures demanded by social program participation as well as basic domestic, care-giving, and self-maintenance activity. 123. Patrick Kampert, When You’re Finished Dusting, We Have a Question for You, CHI. TRIB., Apr. 20, 2008, at C1.

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shown to reduce women’s after-hours workload is a significant increase in wages.124 For every $7,500 in income generated by a female spouse, her weekly chore load reduces by approximately one hour.125 What’s more, this reduction does not appreciably fluctuate based on a male spouse’s income.126 This gender-based time gap, though, does not in itself explain anything about why poor women are more likely to present as obese than their wealthier counterparts. After all, the disparities observed here generally adhere at all income levels.

Instead, the explanation for poverty-obesity disparities may stem from an exacerbation of women’s added time commitments. Specifically, TANF’s work requirements add yet another debt to the time poverty equation. Unfortunately, no empirical research into the aggregate time poverty impact of welfare reform has been published at this time. Nonetheless, circumstantial evidence suggests the problems created by TANF may present a situation of cure worse than the disease. First, consider the issue of transportation. In calculating TANF eligibility, most states cap the “vehicle asset exemption” at one car and many also set an equity cap as well.127 As such, possession of adequate transportation for a female spouse or a vehicle of significant value128 excludes individuals from TANF altogether. Second, consider the work requirement. Single mothers make up the largest contingent of TANF participants and, though aided by a booming economy in the 1990s, face added difficulties with each economic downturn.129 This translates into more time dedicated to low income jobs and, if unemployed, seeking employment to avoid TANF disqualification. Are these observations both speculative and circumstantial? Yes. But are they farfetched? No.

Ultimately, any direct accusation that TANF is “causing” obesity by reducing women’s ability to secure and prepare healthy foods or engage in exercise lacks necessary empirical data support at this time. Still, the intuitive connection between women’s enhanced time pressures combined with stories of difficulty seeking, reaching, and retaining TANF-mandated employment strongly militates in favor of a presumption that TANF is not affording poor women the time—much less the resources—to make healthy choices. Combined with the problem of food insecurity generated by the Food Stamps Program and the general difficulties associated with subsistence in midst of the “food deserts” most participants call home, TANF’s drive to reduce the rolls through heightened participation requirements and greater opportunities for disqualification simply render the pursuit of a healthy weight a secondary goal behind achieving basic subsistence.

124. See Study Links Women’s Earnings with Housework, MSNBC.COM, Nov. 15, 2007, http:// www.msnbc.msn.com/id/21825817. 125. Id. 126. Id. 127. U.S. DEP’T. OF HEALTH & HUMAN SERVS., ADMIN. FOR CHILDREN & FAMILIES, ASSET

PROVISIONS OF STATE TANF PLANS, available at http://www.acf.hhs.gov/programs/ofa/data-reports/annualreport8/chapter12/chap12.htm. 128. Caps on asset value exemption range from $3,899 to $12,000, with most states capping the exemption around $4,500. Id. 129. OFFICE OF THE ASSISTANT SEC’Y FOR PLANNING & EVAL., U.S. DEP’T OF HEALTH & HUMAN

SERVS., RECEIPT OF UNEMPLOYMENT INSURANCE AMONG LOW-INCOME SINGLE MOTHERS 2 (2005).

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IV. GENDERING THE ISSUE: THE UNIQUE CONSEQUENCES OF FEMALE OBESITY

Men, women, and children throughout the United States are obese. Additionally, men, women, and children throughout the United States receive benefits from both SNAP and TANF. Why, then, emphasize the role of social policy in women’s obesity rather than national obesity? Though the answer begins with the readily observable gender gap discussed in Section II, the reasons for isolating gender, poverty, and obesity in this way stem from far graver concerns. Though often called a “disease,” obesity is as much a status as a medical condition. As such, the implications of obesity differ depending upon the other immutable characteristics of the afflicted individual. In the same way that race and gender combine to give rise to specific inferences about intelligence, aggression, and general personality, so too obesity’s consequences are largely shaped—and arguably exacerbated—by gender.

To illustrate this point and the importance of taking on the policy failures discussed in Section III, this Section will consider the unique toll exacted by obesity upon women. Part A will consider the added medical harms experienced by women ranging from heightened rates of high blood pressure and diabetes to issues of infertility and cancer. Part B will consider the social implications of being an obese American woman, including: 1) the weight wage gap; 2) the presumption of unfitness; and 3) the problem and implications of diet hysteria. Finally, Part C will consider the implications obesity discrimination may have for the advances in gender equality secured by Title VII as well as the need to view many forms of obesity discrimination as unlawful gender discrimination.

A. Adding to the Medical Toll

Medically, obesity has been identified as the source of various disorders, conditions, and other diseases affecting almost every part and function of the human body. 130 From readily apparent correlations to hypertension to more surprising links to conditions like breast or colon cancer, the implications of being obese are both pervasive and severe.131 Yet recent reviews of how obesity actually manifests these harms suggest that the burdens of obesity are not borne equally by the sexes. Instead, women disproportionately suffer from the medical consequences of obesity above and beyond the heightened rates expected as a consequence of the obesity gender gap.

The impact of obesity on women has been carefully measured regarding a variety of conditions. The relative risk experienced by obese women exceeded that of similarly situated obese men for Type 2 diabetes, hypertension, and, as women crossed the threshold between overweight and obesity, coronary heart disease.132 Additionally, Polycystic Ovary Syndrome, a condition only affecting

130. Health Consequences, CTRS. FOR DISEASE CONTROL & PREVENTION, http://www.cdc.gov/ nccdphp/dnpa/obesity/consequences.htm (last visited Oct. 21, 2010); see also Must et al., supra note 17. 131. CTRS. FOR DISEASE CONTROL & PREVENTION, supra note 130. 132. Frank B. Hu, Overweight and Obesity in Women: Health Risks and Consequences, 12 J. WOMEN'S

HEALTH 163, 166 (2003).

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women, is also positively correlated with obesity.133 Disorders and diseases stemming from obesity often, in turn, lead to heightened susceptibility to even more problems such as cardiovascular disease.134 In short, when isolated, obese women consistently show a greater risk of developing a variety of health depleting conditions than their male counterparts as well as a greater risk of developing secondary conditions.

What about the medical impact of female obesity in the aggregate though? Given the numerous medical conditions tied to obesity, one major peer reviewed study has completed the significant task of breaking down the quantitative impact of obesity-related illness along gender lines. Drawing upon the 2000 Medical Expenditure Panel Survey to obtain quality-of-life information and the 1990-1992 National Health Interview Survey linked to National Death Index mortality figures, a team headed by Peter Muennig, MD, MPH, found that obesity has a dramatically greater impact on the number of female quality-adjusted life years.135 The “quality-adjusted years” measure employed by Muennig and his team sought to overcome the limitations of prior studies focusing only on increased risk of specific conditions and incorporate the psychological toll of obesity in the calculation.136 The study reported that, nationally, obese men lost approximately 1.9 million quality-adjusted life years due to obesity-related illness compared to healthy counterparts whereas obese women lost approximately 3.4 million quality-adjusted life years.137 The disparity in impact—a differential of approximately 1.8 times—far exceeds the 3 to 4 percent obesity gender gap.

Considering the apparent linkage between obesity and social policies targeting poor women, the magnitude of these medical hardships takes on new meaning. If women are being pushed into obesity by the failures of the social safety net, then perhaps the annual medical expenditures on these obesity-related illness—a figure reaching upwards of $78.5 billion dollars per year in 1998138—and valuations on lost quality of life should to be taken into consideration when attempting to mend the holes in that net.

B. Social Considerations: The “Fat” Man versus the “Fat” Woman

Perhaps the most damaging consequences of obesity, though, do not stem from diabetes, hypertension, or even a heightened cancer risk. Instead, perhaps the biggest problem faced by poor obese women is the social punishment and community demands stemming from a simple height-to-weight ratio. Three specific concerns come to the forefront when examining the social consequences of female obesity: 1) the exacerbation of the gender wage gap promoted by obesity; 2) the general presumption of unfitness applied to “obese” women; and

133. Id. at 165. 134. Id. at 163. 135. Peter Muennig et al., Gender and the Burden of Disease Attributable to Obesity, 96 AM. J. PUB. HEALTH 1662, 1662 (2006). 136. Id. 137. Id. at 1664. 138. Economic Consequences, CTRS. FOR DISEASE CONTROL & PREVENTION, http://www.cdc.gov/ nccdphp/dnpa/obesity/economic_consequences.htm (last visited Oct. 21, 2010).

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3) the dangerous complications associated with weight hysteria and the phenomenon of “yo-yo dieting.”

1. The Gendered Obesity Wage Gap and Perpetual Poverty In its most tangible form, the intersection of gender and obesity can be

articulated in terms of dollars and cents. Though also a legal consequence discussed infra, the financial impact of female obesity, perhaps, is better understood as a social force. Driven largely by perceptions of capacity and desirability, the gendered obesity wage gap transcends legal issues of discrimination to inform the ability of poor women to advance out of poverty and, in turn, out of obesity. The suppression of wages experienced by obese women pushes them towards poverty and social welfare programs, thereby exacerbating their individual weight condition, thereby leading to further suppressed wages. Consequently, the gendered obesity wage gap may represent the most tangible explanation of increased obesity among poor women.

In general, women consistently receive lower wages for performing the same work as men. According to the U.S. Department of Labor Bureau of Labor Statistics, women receive approximately just under $0.81 for every $1 earned by a similarly situated man.139 What’s more, disparities in income based on race also track increases in obesity among women with Caucasian women earning more than women of color.140 The reasons explaining this disparity range from gendered notions of the value of work to the perception that male salaries are a necessity for families (whereas female salaries provide for excess or luxury). As it pertains to this discussion, though, the most important explanation stems from the clustering trend in available employment. Generally, women are more likely to fill out low-paying positions, work for an hourly wage, and receive only the federal or state minimum wage for their efforts.141

This problem of the gender wage gap is exacerbated by obesity. The stigma associated with obesity has appreciably increased in recent years despite the rampant spread of overweight and obesity to all segments of the population.142 An examination of the correlation between gender and obesity in Caucasian women143 shows an increasing wage penalty in recent years for those women perceived to be or actually obese.144 In total, the wage penalty associated with

139. BUREAU OF LABOR STATISTICS, U.S. DEP’T. OF LABOR, WOMEN IN THE LABOR FORCE: A

DATABOOK 47 (2007). 140. Id. 141. BUREAU OF LABOR STATISTICS, U.S. DEP’T. OF LABOR, CHARACTERISTICS OF MINIMUM WAGE

WORKERS 2 (2007) (Table 1). 142. David Lempert, Women’s Increasing Wage Penalties from Being Overweight and Obese 1 (U.S. Bureau of Labor Statistics, Working Paper No. 414, 2007), available at http://www.bls.gov/ ore/pdf/ec070130.pdf. 143. The Lempert study did not attempt to associate the wage gap with other race-gender groups. Lempert noted that studies preceding the current obesity boom did not observe a statistically significant correlation between wages and obesity among other race-gender groupings. Additionally, Lempert notes that existing surveys lack sufficient data on other race-gender groups to produce new data sets at this time. An exhaustive search yields no recent studies reexamining the gender-obesity wage gap in relation to other race-gender groups. Id. at 8. 144. Id.

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obesity in women is 7.47 percent on the dollar—nearly doubling the penalty observed in 1981.145 Moreover, this “penalty” on wages directly correlates to successive increases in BMI with the penalty growing larger as women approach and exceed a BMI of 30.146 Yet no male obesity wage penalty exists.147 This “wage penalty,” then, narrowly affects women to further suppress their wages in a marketplace where they are both under-compensated and regularly relegated to the lowest paying jobs available already.

Driven primarily by social perceptions and the possibility of latent employer discrimination,148 the exacerbation of the wage gap caused by obesity raises important questions about SNAP, TANF, and the root causes of obesity in poor women. SNAP and TANF participants are the most likely to work in low wage sectors and to receive the minimum wage.149 Though participants are more likely to be employed now than pre-PRWORA, participants are no more likely to exceed poverty thresholds and, more specifically, single mothers are more likely to backslide into deeper poverty.150 As such, while TANF presumably seeks to reduce poverty, the reality is that TANF is not helping women achieve subsistence levels of income. Taken as a whole, then, TANF programming simply is not sufficient in its current form to overcome the exit barriers preventing women’s escape from poverty and at the same time exacerbates the movement towards obesity among these same poor women.

2. The Presumption of Unfitness: Confronting the “Obesity Myth” In 2002, Jennifer Portnick was fired for being from her position as a

Jazzercise instructor for being presumptively unfit despite exercising regularly, teaching successfully, and never incurring any disciplinary problems.151 According to Jazzercise, Portnick’s 245-pound frame simply did not convey an image of “fitness” and, as a consequence, would be harmful to business.152 Yet Portnick was fit. What caused her termination had nothing to do with her actual fitness but, rather, the presumption of unfitness. The overly simplistic approach to defining obesity on the basis of BMI consistently leads American society to equate a number on the scale with positive or negative health outcomes. Though adopted as a matter of necessity for the purposes of this Article, the BMI-obesity definition spurs on this presumption of unfitness and the discriminatory consequences attached thereto.

As briefly mentioned in Section II, recent scholarship has increasingly taken issue with the use of BMI to define obesity. The foremost example of this rising wave of critical scholarship is the work of Paul Campos. In his book The Obesity

145. Id. at 20. 146. Id. at 21. 147. Id. at 3. 148. See Charles L. Baum, II. & William F. Ford, The Wage Effects of Obesity: A Longitudinal Study, 13 HEALTH ECON. 885, 896-98 (2004); see generally Susan Averett & Sanders Korenman, The Economic Reality of the Beauty Myth, 31 J. HUMAN RESOURCES 304 (1996); Lempert, supra note 143. 149. JANICE PETERSON ET AL., INST. FOR WOMEN’S POL’Y RESEARCH, IWPR PUB. NO. D446, LIFE

AFTER WELFARE REFORM: LOW-INCOME SINGLE PARENT FAMILIES, PRE- AND POST-TANF 1 (2002). 150. Id. at 3. 151. RHODE, supra note 18, at 17-18. 152. Id.

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Myth, Campos argues that increased emphasis on BMI-based views of weight and fat create a general presumption that size automatically creates poor health and limited capacity to perform even basic functions.153 Campos suggests that the “problems” of weight and obesity are not really problems at all. Instead, he devotes the bulk of his discussion to demonstrating the profit-motive driving a dissemination of what he describes as misleading, inaccurate, and plainly deceptive information on health and weight. Campos’s argument goes much further than most other scholars to suggest that the problem of obesity in America is not a problem at all. As an example, when told he is suggesting “we are ‘giving people permission to be fat,’” his response is: “As opposed to what—not giving people permission to be fat?”154 His alternative approach of placing fitness ahead of BMI as the primary focus of policy is not without empirical support in the medical community.155 Ultimately, Campos views obesity as a contrived rather than real “disease” producing very real and very unnecessary social and moral consequences.

While Campos’s argument admittedly takes rejection of obesity orthodoxy to extremes, he has hit upon an important factor in assessing the consequences of obesity. As he puts it, modern obesity orthodoxy has “made us both the fattest people in the developed world, and increasingly miserable about the fact.”156 Even without accepting Campos’s premise that the weight-loss industry has created a false medicalization of obesity, his fundamental assertion that society extends obesity beyond a medical condition into the realm of morality warrants consideration. The presumption of unfitness implied by Campos’s argument and the experiences of overweight or obese individuals like Jennifer Portnick has two important consequences. Most apparently, the presumption of unfitness allows people in positions of authority and power to discriminate against individuals presenting as obese or overweight. As a result, the obese are relegated to lower paying positions preventing their escape from poverty and its obesity-inducing consequences.

At the same time, the presumption of unfitness may now be so ingrained as to create a second factor explaining the persistence and expansion of obesity among the poor. Perhaps not only employers or customers presume the unfitness of those who are overweight. As Campos stresses, one of the biggest problem with social perceptions of obesity is that they skew self-image and promote self-loathing.157 In short, what if those who are already overweight or obese adopt the presumption of unfitness? Unfortunately, no empirical data is available on this topic. Nonetheless, the speculative impact of this highly probable reality is likely extreme. Synergized with the readily observable external presumption of unfitness imposed by employers and customers, an

153. CAMPOS, supra note 18. 154. Id. at 247 (emphasis added). 155. See Timothy R. Wessel et al., Relationship of Physical Fitness vs. Body Mass Index with Coronary Artery Disease and Cardiovascular Events in Women, 292 JAMA 1179, 1186 (2004) (finding that higher self-reported physical fitness scores were independently associated with lower rates of coronary disease and cardiovascular events, notwithstanding BMI). 156. CAMPOS, supra note 18, at 247. 157. Id. at 57-70 (noting the interplay between external shaming and individual behaviors acknowledging that shame).

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internal presumption of unfitness would only exacerbate the limits imposed upon the obese and would promote self-selection for low-paying, easy-access employment—again promoting the obesity-poverty relationship.

3. Weight Hysteria and the Toll of Yo-Yo Dieting The final socially-driven consequence meriting discussion in this context

pertains to the cyclical forces driving perpetual obesity. America is awash in weight hysteria and fad diets. Though all of the preceding discussion has focused on the causes creating obesity, the problem of weight hysteria and yo-yo dieting helps explain one more reason that—once affixed—obesity’s grasp may be impossible to escape for poor women.

Much like Campos, New York Times reporter Gina Kolata counts herself among the skeptics of obesity orthodoxy. Zeroing in on the relationship between weight obsession and dieting, Kolata’s recent book Rethinking Thin presents a compelling picture regarding the inescapable cycle of weight gain and dieting.158 Following the endeavors of a group of dieters participating in a University of Pennsylvania study, Kolata watched as participants’ efforts to exercise, reduce calorie intakes, and avoid obesity-behaviors succeeded only to be followed by weight gains matching or even exceeding what was lost.159 Her observations left a lingering question: if society is living longer and disability rates are down, why is America unable to stop fixating on the number shown on the scale?160 Kolata asserts that the cause of this fixation is a combination of the moralization discussed by Campos, biological impulses creating hunger when people try to fit into inappropriate “ideal weights,” and a genuine lack of individual responsibility for certain obesity outcomes.161

Much like Campos, Kolata may take her rejection of obesity orthodoxy too far and unfairly embrace obesity as inevitable. The foundations of her argument, however, are sound. Americans spend approximately $58.7 billion per year to a diet industry that often offers far more than it can deliver.162 Yet most dieters will promptly gain back any weight lost shortly after reaching their individual goals—a process called “weight cycling.”163 Consequently, the struggle against obesity is difficult even when afforded all necessary resources. Applied to the context of poor women residing in one of America’s food deserts, the odds of successfully affording, participating in, and remaining on a healthy dieting program are slim. At the same time, the national obsession with weight will encourage poor women to find fad alternatives to losing weight to escape the presumption of unfitness only to fail in most cases and end up in a position worse than before. Consequently, the “weight-cycling” phenomenon decried by

158. KOLATA, supra note 18. 159. Id. at 187. 160. Id. 161. See id. at 188. 162. Andrew A. Newman, Judging a Diet Book’s User by Its Bright Pink Cover, N.Y. TIMES, May 28, 2007, at C3. 163. NAT’L INSTS. OF HEALTH, U.S. DEPT. OF HEALTH & HUMAN SERVS., WEIGHT-CONTROL

INFORMATION NETWORK: WEIGHT CYCLING 1 NIH PUBL’N NO. 01-3901 (2008).

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Kolata likely has a more pronounced affect on poor women—further exacerbating the weight problems created by SNAP and TANF participation.

C. Obesity, Gender, and a New Understanding of Title VII

The last important consequence of poor female obesity stems from the legal arena and the hard-fought battles to secure equal employment status for women in the workplace under the aegis of Title VII. Though long neglected, the idea that “obesity discrimination against women is actually gender discrimination” ought to be revived and afforded new consideration. As perhaps the most insidious consequences of female obesity, obese women increasingly find themselves outside the scope of Title VII sex protection. Worse still, no attempt to pursue redress through the Americans with Disabilities Act (ADA) appears likely to slow, much less stop, the retrenching of obese women’s right to equal treatment when compared not to non-obese women but to men.

In the late-1990s, the ADA seemed to present a new means of redressing the growing problem of obesity discrimination. The Equal Employment Opportunity Commission quickly came to the defense of the morbidly obese—the condition of maintaining twice the designated healthy weight—and asserted that extreme obesity constitutes a qualifying disability.164 Building upon this success, scholars began seeing the ADA as possible foothold for combating obesity discrimination as an unlawful act.165 The special category of ADA discrimination encompassing “persons regarded as having a qualifying disability” applied to obesity for the first time in Cook v. Rhode Island Department of Mental Health, Retardation, & Hospitals, and seemed to pave the way for broader applications.166

This effort to expand the ADA to encompass all obese individuals has slowly weakened, however, in the face of an increasingly unreceptive court. For instance, the Sixth Circuit mandates that obese individuals show a physiological cause of their obesity in order to assert an ADA claim.167 This dramatic restriction on even morbid obesity ADA claims has begun to take hold and has spread to other circuits.168 In general, the “personal responsibility” campaign permeating the social conception of present-day obesity not only advances this judicial reasoning, but also reflects a general view that individual rather than collective action is the only acceptable response to obesity.169

Ultimately, though, this decade-long emphasis on the ADA is likely misplaced. Considering women disproportionately bear the brunt of obesity

164. See Brief of the EEOC as Amicus Curiae, Cook v. R.I. Dep't of Mental Health, Retardation, & Hosps., 10 F.3d 17 (1993) (No. 93-1093), 1993 WL 13625007. 165. See Jane Byeff Korn, Fat, 77 B.U.L. REV. 25 (1997). 166. Cook v. R.I. Dep’t of Mental Health, Retardation & Hosps, 10 F.3d 17 (1st Cir. 1993); see also EEOC v. Tex. Bus Lines, 923 F. Supp. 965 (S.D. Tex. 1996). 167. EEOC v. Watkins Motor Lines, Inc., 463 F.3d 436, 442-43 (6th Cir. 2006). 168. See Greenberg v. Bellsouth Telecomms., Inc., 498 F.3d 1258 (11th Cir. 2007); Middleton v. CSX Transp., Inc., 2008 U.S. Dist. LEXIS 24977 (N.D. Fla. Mar. 28, 2008); Dale v. Wynne, 497 F. Supp. 2d 1337 (M.D. Ala. 2007). 169. See Richard A. Epstein, What (Not) to Do About Obesity: A Moderate Aristotelian Answer, 93 GEO. L.J. 1361 (2005); cf. Benforado et al., supra note 64, at 1645 (2004) (discussing the extraordinary challenges undermining an individualized approach to resolving obesity issues).

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discrimination, the idea that obesity discrimination is really gender discrimination—an idea casually set-aside during the nascence of the obesity debate170—should be reconsidered. The correlation between heightened female obesity, difficulties obtaining employment as an obese woman, and wage suppression in excess of that normal gender gap suggests that obesity discrimination is actually gender discrimination in disguise. The cool reception of this idea among many feminist academic circles stems largely from the divisive impact such an approach may have. As one article notes, “if the sixty-two percent of women who are overweight and obese are being systematically discriminated against . . . often times by other women, this discrimination has the potential to be incredibly . . . destructive to women’s overall achievement.”171 While some would still argue that avoiding this threat to a more unified feminist policy outlook is still critical,172 such an approach necessarily acquiesces to the marginalization of the gender discrimination underlying obesity-gender discrimination.

Whether characterized as individual disparate treatment or systemic disparate impact discrimination, the impacts discussed throughout this section and the consistent finding that these impacts are greater among women than men (even accounting for the gender-obesity gap) suggest that women are being discriminated against not only because they are obese but because they are obese women. With a public willing to laugh at “comedic blurbs” mocking the classification of the morbidly obese as disabled,173 the intolerable discrimination based on a suspect classification like gender is being obscured by the intersection with “socially acceptable” discrimination based on weight. Yet this subtle sexism represents one more—and perhaps the most invidious—consequence of being an obese woman in America.

V. CONCLUSION: PREVENTING PUBLIC POLICY-PROMOTED OBESITY

The policies designed to help America’s poor women secure basic subsistence and move out of poverty are pushing them into obesity and inhibiting their efforts to make a better life for themselves. Though no single policy measure or series of corrections to the current SNAP or TANF assistance structure will eliminate the correlation between poverty, gender, and obesity, a few common-sense proposals may be able to address at least the policy-driven gaps. In particular, two major policy shifts may be able to narrow the gender obesity gap as it corresponds to poverty. First, SNAP should continue seeking to expand participation into farmers’ markets while also seeking to develop new methods of attracting supermarkets to America’s food deserts. Second, both the SNAP benefits cycle and TANF eligibility requirements should be revisited by Congress to alleviate the major sources of food insecurity facing program participants. While they are far from comprehensive and cannot address all of the problems created by the current SNAP and TANF administration systems,

170. Korn, supra note 162, at 26-27. 171. Alexandra W. Griffin, Note, Women and Weight-Based Employment Discrimination, 13 CARDOZO J.L. & GENDER 631, 633 (2006). 172. Id. at 656. 173. See Benforado et al., supra note 64, at 1719 n.258.

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these proposals represent the first steps to ensuring that individuals no longer face the clamor of “personal responsibility” without the means to take that responsibility.

A. Water to the Desert: Ensuring Access to Healthy Choices

The easiest aspect of this problem to redress is the limited access to healthy foods facing the residents of various food deserts. Two major strategies can help create an oasis of healthy choices for these citizens. First, the USDA’s pilot farmers’ market program should be expanded and enjoy added incentives. As of 2009, more than 900 farmers markets and farm stands began accepting SNAP benefits in some form.174 These programs operate in a variety of forms including use of EBT cards or, alternatively, exchanging EBT credits for tokens or other currency only redeemable at the farmer’s market.175 Though helpful, these programs will have little effect if individuals must travel as far to reach the farmers’ market as they would to reach the supermarket. As such, the USDA efforts to develop SNAP in the context of farmers’ markets must be paired with an effort to encourage the creation of new markets in states’ various food deserts.

The second option for advancing the availability of healthy choices is the introduction of a combination of new incentive programs and statutory mandates to attract supermarkets to food deserts. Consolidation among supermarkets in recent decades as well as the spread of “super-mega stores” like Wal-Mart has dramatically reshaped the distribution and accessibility of food in poor America.176 These large chains draw away resources and revenue from local retailers until grocery shopping shifts to single centralized locations.177 Yet a combination of statutory restrictions and tax and subsidy incentives could return supermarkets to the segments of the population desperately in need of access to healthier choices than the local McDonalds. First, on the restrictive side, state and federal governments should limit or prohibit the transfer of public assistance funding and subsidies to retailers who have abandoned stores in low-income neighborhoods or who are not within easy access of those neighborhoods.178 These “stick” statutory restrictions should be combined, though, with the “carrot” of incentive packages. By carefully crafting tax credits and exemptions, as well as the provision of public subsidy, for the construction and operation of supermarkets in low-income neighborhoods, supermarket chains will again have reason to set up shop in the food deserts around the country.

174. USDA AGRIC. MKTG. SERV. ET AL., SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM (SNAP)

AT FARMERS MARKETS, A HOW-TO HANDBOOK 3 (2010), available at http://www.ams.usda.gov/ AMSv1.0/getfile?dDocName=STELPRDC5085298&acct=wdmgeninfo. 175. Id. at 1. 176. KATY MAMEN, THE OAKLAND INST., POL’Y BRIEF 1(3), FACING GOLIATH: CHALLENGING THE

IMPACTS OF SUPERMARKET CONSOLIDATION ON OUR LOCAL ECONOMIES, COMMUNITIES, AND FOOD

SECURITY 1 (2007). 177. Id. at 3-4. 178. Id. at 7 (proposing that public aid be limited to those companies paying employees a “living wage”).

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In short, SNAP can only produce healthy citizens when those citizens can get healthy food. By developing the growing farmers’ market sector and working with major supermarket chains, that access can be a reality for the more than 25 percent of SNAP participants lacking access to dietetic foods.

B. Combating Uncertainty: Limiting Policy-Driven Food Insecurity

The other major problem facing SNAP and TANF participants is program-created food insecurity. Considering the strong linkage between food insecurity and obesity, revisions to both programs alleviating participants’ stability concerns will certainly aid in the effort to combat participant obesity. Regarding SNAP, the easiest and most cost-effective way of reducing the imposition of SNAP food insecurity is altering the benefits delivery schedule. For TANF participants, the sources of the food insecurity problem are at the heart of PRWORA’s core purposes—making the obstacles to change much more severe. Nonetheless, the effort to reduce obesity among the ranks of TANF need not eliminate the time limits and work requirements of PRWORA. Instead, by introducing a new measure of administrative discretion in how to apply PRWORA’s rules, TANF participants may be able to escape the perpetual instability associated with their program participation.

In order to reduce food insecurity, the SNAP cycle should be split to correspond with typical pay cycles. The current system only pays out benefits at the beginning of each month and then places responsibility for budgeting the use of the benefits on participants. This long-range budgeting likely represents the primary source of food insecurity among participants.179 By splitting the benefits cycle from a monthly into a semi-monthly regime, SNAP administrators will be able to accomplish two important advances. First, participants will no longer be forced to bear responsibility of budgeting their benefits over a four-week period. Instead, for many, their benefits payments will correspond with wage payments and create a sense of greater stability. Second, the impact of any participant failures to properly budget benefits will be dramatically reduced and, as a consequence, such failures will be less likely to create long-term food insecurity associated with SNAP participation. As such, for the administrative cost of distributing two rather than one round of electronic benefits, much of the food insecurity attached to SNAP participation could be eliminated.

While certainly more complex, the food insecurity problems created by TANF’s requirements are also at least partially remediable through the introduction of minor changes to the general program. Ideally, the instability and insecurity associated with TANF could be eliminated by a removal or dramatic extension of the lifetime limits as well as a dramatic reduction in the number of hours included in the so-called “welfare to work” requirement. Realistically, any wholesale attack on these requirements is simply not politically viable. As such, TANF’s food insecurity issues must be addressed indirectly.

The best indirect method of reducing food insecurity is affording state administrative programs new discretion in assessing the fulfillment of TANF

179. Wilde, supra note 103, at 1399.

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requirements. If participants must be bussed two hours each way to and from work, states should be able to count some or all of that time towards the 30-hour requirement. If a given neighborhood sees increasing numbers of participants drop off the TANF roles due to the time limits rather than successful movement out of poverty, states should be empowered to extend the lifetime limit on a case-by-case basis. Such an introduction of administrative discretion would accomplish two important tasks. First, it would help offset the increasing time poverty experienced by TANF participants thereby enabling more time expenditures on securing and preparing healthy foods as well as engaging in fitness activities. Second, it would remove the “ticking clock” from TANF and enable hardworking participants the opportunity to receive benefits so long as their participation meets state minimums.

“Healthy living” is only a choice when subsistence is assured. By correcting the shortcomings in SNAP benefits distribution and TANF’s arbitrary boundaries, the problem of food insecurity—a key problem underlying obesity among poor women—can be substantially reduced among participants in both social programs.

C. Taking on the Intersection Gender, Poverty, and Obesity

The problem of obesity among poor women is complex and multifaceted. Certainly, additional empirical research on issues like time poverty and welfare reform as well as the internalization of the presumption of unfitness is needed to gain a fuller understanding of how SNAP and TANF work to create obesity in this segment of the population. Nonetheless, this Article has attempted to illuminate some of the facets of the obesity issue and focus on just a few ways that public policy can be reshaped to help poor women break free of obesity and its attendant health, social, and legal consequences with an ultimate aim of helping create paths out of poverty. By taking the time to move beyond discrete categories of classification and consider the important intersections between things like race, gender, and poverty, previously hidden issues like those presented here become both observable and manageable. Approached in this way, even a massive issue like the spread of obesity to a huge contingent of the population can be understood not only as an important medical concern but, more importantly, as a reflection of social values and polices effecting the daily lives of America’s least advantaged women.

getting fat on government cheese: the connection between

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